Waldo: South America

Waldo, Hansen’s ROW trend, is not in Africa nor in Antarctica. Is Waldo in South America?

Here we are referring to a trend calculated according to the stated methodology of Hansen et al 1999, 2001, in which urbanization effects are supposedly removed by coercing trends to trends of rural stations. For that purpose, I am assessing the availability of rural stations which go back to the 1930s – thereby permitting a comparison of 1934 to 1998 in these other regions under Hansen’s adjustment – while also having sufficient information to permit a 1961-1990 normal to be calculated.

South America has a land area of 17.8 million km2 (about 12% of the world’s land surface) and is over twice the size of the contiguous 48. There are 7 stations with records that include all the 1930s, shown below together with their anomaly average. I noticed that 6 stations start in 1931 and I show them below separately.

Three of the stations are islands: Isla Juan Fernandez, Isla Huafo and Grytviken (South Georgia) – only 4 on the mainland. The first two (columnwise) are in Argentina, Q is in Brazil, the next 3 in Chile and the last is again South Georgia. Punta Arenas is quite far south (53 S) and provides an interesting counterpoint to the shorter records from the Antarctic Peninsula, showing strong warming since the 1940s.

Obviously several of the records have major discontinuities. We know from the U.S. HCN analyses that very slight changes in station location can create biases that Karl needs to adjust through his TOBS adjustment, MMTS adjustment, station history adjustment etc. and that in the U.S. these station adjustments are not small (actually a collation of USHCN adjustments needs to be made to get a distribution to specify the distributions that might be at work when one ventures to other countries. Is there a possibility that, for example, some discontinuity occurred at Isla Huafo or Quiaca during the decades long interval between measurements? Seems to me to be at least a possibility? If one is taking an average, this becomes relevant because the later values of Quiaca show a step increase towards the end not apparent in the continuous series – which gets reflected in the average.

On a larger scale, here is the average of the seven long records (bottom right hand red above):

For completeness, here is the average of the six records commencing in 1931:

A few posters are criticizing me for apparently focusing on areas with poor coverage. I don’t think that anyone can accuse me of not discussing American stations in sufficient detail – so this is a little unfair. I’ve posted extensively earlier in the year on China and Russia and passim on Australia. I’ll probably get to them again. But there’s only so much that I can do. If a critic feels that some area with good records is being given short shrift because I haven’t got to it yet, please feel free to write a post of detail equivalent to mine and I;ll post it.

Is it just me or does La Quiaca seem to have an anomalous jump circa 2000, after several years of being offline? I wonder if the station went down, then got replaced with one of them nifty HG-83 thermometers?

South Georgia Island shouldn’t be included in South America, Steve. If anything, it is more in the Antarctica region. I note that the Antarctic sea ice extends right up to South Georgia Island right now (even though it is 800 miles from the tip of the Antarctica pennisula.)

Almost all of the GW indicated by the surface record seems to come from the Arctic region.

Not from what I’ve seen. Most of the warming attributed to the Arctic is actually from sub-Arctic records. How many of the Arctic records are continuous measurements from 1931 to 1998? Given that most Russian and Canadian station records end in 1989/1990…

IIRC the Greenland records show the 1930’s were warmer than the 1990 pluses.

The station is located in La Quiaca Meteorological and Geomagnetic Observatory (Lat: 22º 06 13 S ; Lon: 65º 36 00 W). La Quiaca city is situated at the North of Jujuy province in the Argentinean Puna. The observatory is at an altitude of a 3483m. a.s.l. within an enclosure of about 36000m2 .The vegetation in the surrounding area is very sparse. Close to the Station there is a street open to public traffic and sometimes an intense traffic can be observed. The main bus stop of the city is located just opposite the observatory.

The doc contains a couple of poor quality images of the met station on page 40. The above description may be the most useful part, though.

#24 Rob
John Daly had an early blog where he simply put up urban and rural sites side by side and showed the huge potential impact of UHI effects on the temperature record. Michael Crichton used the same technique. I get the sense that he was one of the earlier and more vociferous skeptics. Alas he passed away at a relatively young age in 2004. Our Australian correspondents can provide more details.

Not to complicate matters but does not Waldo change his name as he goes from region to region. NA Waldo is regional so why cannot climate trends be also? But then again that’s the punchline we await from Waldo, Wally, Charlie, Effy, etc.

I did a brief study of three 5×5 degree grids in South America. Since the IPCC calculates the average temperature in each 5×5 degree grid and then averages the grids, it helps to look at the data in terms of these “squares”. I have combined the AR4 figure showing “observed” trend with the Columbia University station Google Map along with GISS stations and average charts for the grids from the GHCN data. The devil is certainly in the details, since the warming in the data (or lack thereof) just doesn’t seem to match what the IPCC says. No Waldo.

….thank Steve and climateauditors if they actually find something useful, assess it and assimilate it, and move on.

says Judith Curry at RC, after the Borg “resistance is futile” school.

They are characterized by relentless pursuit of targets for assimilation, their collective consciousness that enables rapid adaptability to almost any defence, and the ability to continue functioning properly despite seemingly devastating blows.

Alan
Very interesting analysis with very effective visuals. I found this site in looking for population numbers for Steve’s look at African rurla sites, A quick look at a few of your sites in Argentina suggests that few if any of them meet the GISS definition of rural. It would be great to overlay the GISS charts with population numbers. I know it isn’t perfect but it would surely help to illustrate the need to genuinely address the UHI trend effect and the unrepresentative nature of the station selection.

One last thought on La Quiaca, Argentina. It’s right on the Bolivian border and looks to be quite a nexus of people traveling into and out of Bolivia. Google Earth the border crossing then scan along the road southward. You can see a line of dots like ants on the march to/from the border and then all those busses. I suspect there’s more to this story than what the graph, above, tells us. M. Simon: I’m sorry – perhaps someone else can answer your question about lapse rate?

I have crossed the Bolivian/Argentine border at La Quiaca several times, once spending four or five hours in the vicinity of the bus station waiting for a connecting bus to Mendoza. The striking thing when one crosses the border is th amount of asphalt and concrete on the Argentine side of the border. There is not a lot of such development by American standards, but to one used to Bolivia (I was a Peace Corps volunteer at the time) it seems like a big jump forward in development. When I was down there in 1998-2000 Villazon, on the Bolivian side had only a few asphalted streets, and a few more with cobblestones, while all of the major streets in La Quiaca were paved. Still, that is a poor part of Argentina, and I would guess that few of the houses (all of which would be adobe or masonry construction) have a source of heat beyond a small gas stove used for cooking. There were, however, lots of big Volvo and Mercedes diesels idling at the Bus Station, and lots of cargo truchs lined up to cross the border.

No, lapse rates are definitely not actual constants. Lapse rates are defined as nominal values for purposes of use in models that are attempting to estimate a result. Nominal lapse rates are variable with respect to an array of changes in the environment ranging from annual changes in season to daily changes in humidity. Actual lapse rates are highly variable and are often significantly different from the nominal lapse rates defined for a given geographical location whenever atmospheric conditions such as temperature inversions occur. Atmospheric models, which must recognize the fact that air temperatures do not always decrease with increasing altitude and decreasing air pressure, demonstrate how nominal lapse rates used for modeling atmospheric conditions is highly variable and do not always reflect reality and actual conditions.

The methods used to apply — nominal lapse rates — used in atmospheric models across diverse geographic and seasonal situations is a potantial source of error when applied as adjustments to the raw observed temperatures and other climatological data. See NASA and other sources for explanations of how they define and use lapse rates with respect to climatological data such as air temperatures.

I like using the spatial maps at GCAG to get an idea of just what is — or really is not — known about “global” variations in temperature over time. Since we are looking for Waldo in “long” series going back to 1930, here is an animation I created for maximum temperatures, June through October, 1930-2004, from the GHCN Land Surface Data Set.

The spatial distribution of the Waldo is remarkable. The Waldo is nowhere to be found in South America. In Africa, you have to look real hard to see where the Waldo might have been, briefly. The Waldo is missing from most of central Asia, as well. In North America, however, the Great Blue Waldo can be spotted over most of the US. The Lesser Red Waldo seems confined mostly to Europe, Western Australia, and Japan. It is not known, though, whether these are true Red Waldos, because of influence of urban heat islands on the Waldo, which is known to make a Blue Waldo appear to be a Red Waldo, when it really isn’t.

The Global Waldo, believed by many to be a species of Red Waldo, appears to be largely mythical. There may, though, be a hypothetical Albino Waldo, which is neither red nor blue, but something in between.

“The 1960 census counted almost 140,000 residents in the new Federal District; by 1970 this figure had grown to more than 537,000. In 2000 the population of the Brazilian Federal District stood at more than two million.”

and

“The Federal District, were Brasília is located, is considered to have one of the highest growth rates in Brazil. Its population increases an average of 2.82% each year. The vegetation surrounding the city is called “cerrado”, the South American savanna.”

and

“The Human Development Index in the city is at 0.844 (developed nation level)….”

Regarding the trend of the 6 stations, what happens if you do a regression? Just by eyeballing,
it looks like most of the data prior to the 1970’s are below the 0 line, while at least half since
that time are above the 0 line. I know Hansen is claiming a 0.34C or thereabouts temperature increase over the last century, and if there is any trend at all in this data, it looks like it could be maybe half that value. I do realize that my eye might just be fooled by the dip in the 1950’s, and that the data don’t consider possible biases… just wondering.

BTW, this site is fantastic! I’ve been lurking here for several months and am amazed that nobody seems to have done this type of analysis before. Someone is finally telling the Emperor to put some clothes on.

#55. HAnsen purports to deal with urban bias. The question is what he actually did and whether what he actually did is sufficient to deal with urban bias. It looks to me like it doesn’t. But one needs to parse the calculations.

#57 Steve: Thanks for the reply. I do understand completely what you are doing with all the Waldo investigation. My point is that in this thread, everyone is concluding that Waldo, aka the ROW warming trend, isn’t here in South America. It looked to me that there could possibly be a warming trend in the 6 station data, and everyone in this thread is glossing over that.

I also understand that all of this data could be corrupted by UHI, making the data suspect anyway.

Apparently, the reliability questions of surface temperature stations has been taken up by John Vliet, a Canadian software developer and mathematician. He compared “the official NASA GISTEMP record the temperature record from the sites identified as both good quality (rated one, two, or three) and rural. The results were surprising to many in the Climate Audit community, as they found that the GISTEMP record matches the best site rural record quite well.”

If I understand that correctly, John Vliet used what SurfaceStations.org described as rural and good quality. I realize that the audit is only one-third complete, but does Vliet’s work suggest that NASA is giving us reliable surface composite temperature?